conduitR


Overview
conduitR is an R package that provides tools for metaproteomics
analysis using conduit and conduit-GUI. It offers a comprehensive suite
of functions for processing, analyzing, and visualizing metaproteomics
data. These functions are designed to be used in conjunction with the conduit and conduit-GUI packages,
or independently for custom analyses.
Features
Getting Data
- Download FASTA files from UniProt and NCBI
- Download and process taxonomy data from NCBI
- Manage and combine multiple proteome databases
Data Processing
- Create custom protein sequence databases
- Associate sample proteomics data and metadata using QFeatures
integration
- Transformation, imputation, and normalization of proteomics
data
- Quality control and filtering options
Statistical Analysis
- Perform LIMMA differential expression analysis
- Support for various machine learning models:
- LASSO regression
- Random Forest
- XGBoost
- Feature importance analysis and selection
- Statistical testing and multiple testing correction
Visualization
- Interactive heatmaps with customizable annotations
- PCA biplots with flexible aesthetics
- Taxonomic visualizations:
- Barplots for abundance analysis
- Heat trees for hierarchical relationships
- Volcano plots for differential expression
- KEGG pathway visualization
- Feature-specific plots
- Custom plot aesthetics and themes
Miscellaneous
- Comprehensive logging functions
- Error handling and validation
- Integration with existing bioinformatics workflows
Dependencies
The package requires the following R packages: - QFeatures for
proteomics data management - limma for statistical analysis - ggplot2
for visualization - tidyr and dplyr for data manipulation - Additional
packages for specific functionalities (see DESCRIPTION file)
Installation
You can install the development version of conduitR from GitHub:
r, eval = FALSE # install.packages("devtools") devtools::install_github("baynec2/conduitR")
Usage
This is a work in progress. The package documentation and vignettes
will be updated with detailed examples demonstrating: - Data import and
preprocessing - Statistical analysis workflows - Visualization
techniques - Integration with conduit and conduit-GUI - Best practices
and recommendations
Stay tuned for updates!